Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models

• Main Authors: Seera, M., Lim, C.P., Liew, W.S., Lim, E., Loo, C.K.
• Format: Article
• Language: English
• Published: PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND 2015
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/13942/1/Classification_of_electrocardiogram_and_auscultatory_blood_pressure.pdf; http://eprints.um.edu.my/13942/; http://ac.els-cdn.com/S095741741400801X/1-s2.0-S095741741400801X-main.pdf?_tid=bacd29d8-e7cf-11e4-a4fa-00000aab0f6c&acdnat=1429584190_a9c034bfc0490d7fb60fc36edb602f9c

In this paper, two real-world medical classification problems using electrocardiogram (ECG) and auscultatory blood pressure (Korotkoff) signals are examined. A total of nine machine learning models are applied to perform classification of the medical data sets. A number of useful performance metrics...